Evaluating the End-User Experience of Private Browsing Mode

Nowadays, all major web browsers have a private browsing mode. However, the mode's benefits and limitations are not particularly understood. Through the use of survey studies, prior work has found that most users are either unaware of private browsing or do not use it. Further, those who do use private browsing generally have misconceptions about what protection it provides. However, prior work has not investigated \emph{why} users misunderstand the benefits and limitations of private browsing. In this work, we do so by designing and conducting a three-part study: (1) an analytical approach combining cognitive walkthrough and heuristic evaluation to inspect the user interface of private mode in different browsers; (2) a qualitative, interview-based study to explore users' mental models of private browsing and its security goals; (3) a participatory design study to investigate why existing browser disclosures, the in-browser explanations of private browsing mode, do not communicate the security goals of private browsing to users. Participants critiqued the browser disclosures of three web browsers: Brave, Firefox, and Google Chrome, and then designed new ones. We find that the user interface of private mode in different web browsers violates several well-established design guidelines and heuristics. Further, most participants had incorrect mental models of private browsing, influencing their understanding and usage of private mode. Additionally, we find that existing browser disclosures are not only vague, but also misleading. None of the three studied browser disclosures communicates or explains the primary security goal of private browsing. Drawing from the results of our user study, we extract a set of design recommendations that we encourage browser designers to validate, in order to design more effective and informative browser disclosures related to private mode

Responsive behavior in tutorial spoken dialogues

Humans are very good at detecting subtle affective changes in a person while speaking with them. A good conversational partner is able to not only detect these changes, but also alter their own way of speaking to suit the needs of their partner. This is especially true in one-on-one tutoring, where the attitude of the student affects the amount of learning that occurs. In this study, I used several methods to develop a model, based on a human tutor, which uses the student\u27s actions (in the form of dialog history, prosody, and utterance timing) and feelings to determine an appropriate response choice. I then asked several participants to receive tutoring from a Wizard-of-Oz spoken dialog system that uses my model to generate acknowledgments and a similar system the randomly generates acknowledgments. I found that while there was no significant difference between the two systems in either the amount of learning or user preference, participants tended to prefer the rule-based system

Acknowledgment Use with Synthesized and Recorded Prompts

Acknowledgments, e.g., “yeah” and “uh-huh,” are ubiquitous in human conversation but are rarer in human-computer interaction. What interface factors might contribute to this difference? Using a simple spoken-language interface that responded to acknowledgments, we compared subjects’ use of acknowledgments when the interface used recorded speech with that seen when the interface used synthesized speech. Contrary to our hypothesis, we saw a drop in the numbers of subjects using acknowledgments: subjects appeared to interpret the recorded-voice interface as signalling a more limited interface. These results were consistent for both Mexican Spanish and American English versions of the interface

Toward Building Conversational Spoken-Language Interfaces: Acknowledgment Use in American English and Mexican Spanish

Should spoken-language interfaces incorporate human discourse phenomena? Acknowledgments, for example, are ubiquitous in human conversation but are rare in human-computer interaction. Are people unwilling to use this human convention when talking to a machine, or is their scarcity due to the design of current spoken-language interfaces? We found that, given a simple spoken-language interface that responded to acknowledgments, over two thirds of subjects used acknowledgments at least once, about the same number that used more traditional commands to control the interface. These results were consistent for both Mexican Spanish and American English versions of the interface, and they suggest that it may be possible to make use of human discourse mechanisms such as acknowledgment to build more flexible spoken-language interfaces

AcknowledgC47 Use with Synthesized and Recorded Prompts

Acknowledgments e.g., "yeah" and "uh-huh," areubiquitous in human convers2O;u but are rarer in human-computer interaction. What interface factors might contribute tothis difference ? Use? as66fl; s66 en-language interface thatresu92O1 to acknowledgments we comparedsredu90; us of acknowledgments when the interface usu recordedscord with that sat when the interface usu su626fl6uI; su626 Contrary to our hypothes;6 we s w a drop in thenumbers ofsu6O779 us6O acknowledgments sgments appeared to interpret the recorded-voice interfaceas su6fl12fluI a more limited interface. Thes res67 werecons612;u for both MexicanSpanis and American Englis vers01O of the interface. 1. I troductio Spoken-language interfaces which allow one to talk to a computer applicationinslic of typing or clicking, are beginning to move from the laboratory to the real world. In addition to offeringhands6fl6fl acces tothos who cannot or prefer not to us a traditional keyboard interface, se, en-languagesn-lan have gained popularity intelephone-basu applications spp as airline information stionu9 The quality of interaction offered by thes interfaces however,is far from that offered by a human operator. Current-generation interfaces areseu; relatively fragile. To reduce errors desrs61 ofsu6 en-languagesn- tems createprompts that guide the usu towardsdu;) focus)6 in-vocabularyresyu67O (e.g., Bas.,u et al., 1996; Cole, et al., 1997). Oneres6fl ofthis approachis the deliberate sliberateu of dialogue behaviors that, in human convers20fluI manage and coordinate the convers -uO;0 Ines77O70 the computeris always in charge of the flow of the convers0OOuI Whilethis may be adequate, even appropriate, for limitedtast ss as checking for flightdelays we would like to move toward moresreuO1 ticatedsca en-language interface..

Usability Inspection Methods after 15 Years of Research and Practice

Usability inspection methods, such as heuristic evaluation, the cognitive walkthrough, formal usability inspections, and the pluralistic usability walkthrough, were introduced fifteen years ago. Since then, these methods, analyses of their comparative effectiveness, and their use have evolved in different ways. In this paper, we track the fortunes of the methods and analyses, looking at which led to use and to further research, and which led to relative methodological dead ends. Heuristic evaluation and the cognitive walkthrough appear to be the most actively used and researched techniques. The pluralistic walkthrough remains a recognized technique, although not the subject of significant further study. Formal usability inspections appear to have been incorporated into other techniques or largely abandoned in practice. We conclude with lessons for practitioners and suggestions for future research